229 related articles for article (PubMed ID: 36190117)
21. Multi-task autoencoder based classification-regression model for patient-specific VMAT QA.
Wang L; Li J; Zhang S; Zhang X; Zhang Q; Chan MF; Yang R; Sui J
Phys Med Biol; 2020 Nov; 65(23):235023. PubMed ID: 33245054
[TBL] [Abstract][Full Text] [Related]
22. Comparison of DVH-based plan verification methods for VMAT: ArcCHECK-3DVH system and dynalog-based dose reconstruction.
Saito M; Kadoya N; Sato K; Ito K; Dobashi S; Takeda K; Onishi H; Jingu K
J Appl Clin Med Phys; 2017 Jul; 18(4):206-214. PubMed ID: 28649722
[TBL] [Abstract][Full Text] [Related]
23. Application of dose-volume histogram prediction in biologically related models for nasopharyngeal carcinomas treatment planning.
Cao W; Zhuang Y; Chen L; Liu X
Radiat Oncol; 2020 Sep; 15(1):216. PubMed ID: 32933543
[TBL] [Abstract][Full Text] [Related]
24. TransQA: deep hybrid transformer network for measurement-guided volumetric dose prediction of pre-treatment patient-specific quality assurance.
Zeng L; Zhang M; Zhang Y; Zou Z; Guan Y; Huang B; Yu X; Ding S; Liu Q; Gong C
Phys Med Biol; 2023 Oct; 68(20):. PubMed ID: 37714191
[No Abstract] [Full Text] [Related]
25. Pretreatment patient-specific IMRT quality assurance: a correlation study between gamma index and patient clinical dose volume histogram.
Stasi M; Bresciani S; Miranti A; Maggio A; Sapino V; Gabriele P
Med Phys; 2012 Dec; 39(12):7626-34. PubMed ID: 23231310
[TBL] [Abstract][Full Text] [Related]
26. Prediction of patient-specific quality assurance for volumetric modulated arc therapy using radiomics-based machine learning with dose distribution.
Ishizaka N; Kinoshita T; Sakai M; Tanabe S; Nakano H; Tanabe S; Nakamura S; Mayumi K; Akamatsu S; Nishikata T; Takizawa T; Yamada T; Sakai H; Kaidu M; Sasamoto R; Ishikawa H; Utsunomiya S
J Appl Clin Med Phys; 2024 Jan; 25(1):e14215. PubMed ID: 37987544
[TBL] [Abstract][Full Text] [Related]
27. Direct Dose Prediction With Deep Learning for Postoperative Cervical Cancer Underwent Volumetric Modulated Arc Therapy.
Yu W; Xiao C; Xu J; Jin J; Jin X; Shen L
Technol Cancer Res Treat; 2023; 22():15330338231167039. PubMed ID: 36999201
[TBL] [Abstract][Full Text] [Related]
28. The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer.
Qilin Z; Peng B; Ang Q; Weijuan J; Ping J; Hongqing Z; Bin D; Ruijie Y
J Appl Clin Med Phys; 2022 Jun; 23(6):e13583. PubMed ID: 35262273
[TBL] [Abstract][Full Text] [Related]
29. Dosimetric features-driven machine learning model for DVH prediction in VMAT treatment planning.
Ma M; Kovalchuk N; Buyyounouski MK; Xing L; Yang Y
Med Phys; 2019 Feb; 46(2):857-867. PubMed ID: 30536442
[TBL] [Abstract][Full Text] [Related]
30. Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours.
Guerreiro F; Seravalli E; Janssens GO; Maduro JH; Knopf AC; Langendijk JA; Raaymakers BW; Kontaxis C
Radiother Oncol; 2021 Mar; 156():36-42. PubMed ID: 33264639
[TBL] [Abstract][Full Text] [Related]
31. Patient specific quality assurance of volumetric modulated arc therapy of synchronous bilateral breast cancer.
Djoumessi Zamo FC; Njeh CF; Colliaux A; Blot-Lafond V; Moyo MN
Med Dosim; 2023 Dec; ():. PubMed ID: 38071091
[TBL] [Abstract][Full Text] [Related]
32. Site-agnostic 3D dose distribution prediction with deep learning neural networks.
Mashayekhi M; Tapia IR; Balagopal A; Zhong X; Barkousaraie AS; McBeth R; Lin MH; Jiang S; Nguyen D
Med Phys; 2022 Mar; 49(3):1391-1406. PubMed ID: 35037276
[TBL] [Abstract][Full Text] [Related]
33. A method for a priori estimation of best feasible DVH for organs-at-risk: Validation for head and neck VMAT planning.
Ahmed S; Nelms B; Gintz D; Caudell J; Zhang G; Moros EG; Feygelman V
Med Phys; 2017 Oct; 44(10):5486-5497. PubMed ID: 28777469
[TBL] [Abstract][Full Text] [Related]
34. Modeling of multiple planning target volumes for head and neck treatments in knowledge-based treatment planning.
Zhang J; Ge Y; Sheng Y; Yin FF; Wu QJ
Med Phys; 2019 Sep; 46(9):3812-3822. PubMed ID: 31236943
[TBL] [Abstract][Full Text] [Related]
35. Patient-specific quality assurance prediction models based on machine learning for novel dual-layered MLC linac.
Zhu H; Zhu Q; Wang Z; Yang B; Zhang W; Qiu J
Med Phys; 2023 Feb; 50(2):1205-1214. PubMed ID: 36342293
[TBL] [Abstract][Full Text] [Related]
36. Deep learning-based tools to distinguish plan-specific from generic deviations in EPID-based in vivo dosimetry.
Olaciregui-Ruiz I; Simões R; Jan-Jakob S
Med Phys; 2024 Feb; 51(2):854-869. PubMed ID: 38112213
[TBL] [Abstract][Full Text] [Related]
37. Individual volume-based 3D gamma indices for pretreatment VMAT QA.
Yi J; Han C; Zheng X; Zhou Y; Deng Z; Xie C; Jin X; Jin F
J Appl Clin Med Phys; 2017 May; 18(3):28-36. PubMed ID: 28318101
[TBL] [Abstract][Full Text] [Related]
38. A robust approach to establish tolerance limits for the gamma passing rate-based patient-specific quality assurance using the heuristic control charts.
Xiao Q; Bai L; Li G; Zhang X; Li Z; Duan L; Peng R; Zhong R; Wang Q; Wang X; Bai S
Med Phys; 2022 Feb; 49(2):1312-1330. PubMed ID: 34778963
[TBL] [Abstract][Full Text] [Related]
39. Implementation of TG-218 for patient-specific quality assurance tolerance and action limits determination: Gamma passing rate evaluation using 3DVH software.
Stasinou D; Patatoukas G; Kollaros N; Diamantopoulos S; Kypraiou E; Kougioumtzopoulou A; Kouloulias V; Efstathopoulos E; Platoni K
Med Phys; 2022 Jul; 49(7):4322-4334. PubMed ID: 35560362
[TBL] [Abstract][Full Text] [Related]
40. Combining dense elements with attention mechanisms for 3D radiotherapy dose prediction on head and neck cancers.
Cros S; Bouttier H; Nguyen-Tan PF; Vorontsov E; Kadoury S
J Appl Clin Med Phys; 2022 Aug; 23(8):e13655. PubMed ID: 35661390
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
